Data science is the process of collecting, storing, categorizing, and analyzing data to aid businesses in making data-driven choices. It's widely used by seasoned computer specialists with a wide range of technical skills. A collection of data exists in every technological interaction.
Data Science is one of the most in-demand fields today. The demand for data scientists has increased by 300% since 2012 and is expected to grow even more in the next decade.
The reason for this is that companies need to make sense of their data and use it to improve their business processes. The methods used to do this can be anything from predictive modeling to using machine learning algorithms to extract insights from the data.
Data Scientists are specialists in gathering, analyzing, and visualizing data to uncover important trends, predict issues, and make smarter decisions. They're also skilled at developing models that can forecast future results.
Data science is an umbrella term that encompasses various disciplines such as statistics, computer science, artificial intelligence (AI), machine learning, and predictive analytics. The main goal of these disciplines is to find insights from raw data using statistical modeling techniques.
If you're seeking the greatest organizations in the United States that are hiring data scientists, you've come to the perfect spot!
Let us begin by understanding why is data science so Important in today's World?
The Increasing Need for Data Science
Data science helps us make sense of the enormous amount of information we are bombarded with every day. It can be used for everything from analyzing traffic patterns to tracking social media trends. It also helps businesses make better decisions about their business model and marketing strategy.
Data Science has become an integral part of many industries and businesses, especially in the manufacturing, banking, and finance sectors. In the healthcare industry, it has been used to streamline the treatment process for patients by improving their experience.
The demand for data science skills has been on the rise in recent years as companies have started investing heavily in analytics, machine learning, and artificial intelligence (AI). According to a survey by Tractica, global spending on AI will generate revenues of $59.8 billion by 2025.
Data scientists have become an important commodity in today's job market. Many companies are going out of their way to recruit talented data scientists because they know how important it is to have people who can analyze and interpret data effectively!
Due to the rise of Big Data, the scope of Data science is constantly increasing. With each passing day, more and more data is being available to mankind, And with it more and more experts who can analyze and make sense of that data are coming into high demand.
As more companies realize the value of data, the need for data scientists will only grow. And to be on the leading end in this era, we need to understand that data is the best tool at our disposal.
Key Skills required in Data Science
Being a data scientist demands a wide range of abilities. For various reasons, every sector and organization requires a data scientist. However, there is a basic structure that specifies the core skills needed to be an effective data scientist. These abilities will make you a top choice for any business trying to expand through data-driven decisions.
Statistical Knowledge:
Statistics is the science of drawing presumptions from data sets based on their size and complexity. Data scientists employ statistical approaches across sectors to extract insights from massive amounts of data generated during trials or surveys. Statistics is an extremely valuable ability to have, and recruiters expect every applicant to possess it. So, before applying for any data science jobs, make sure you have a decent knowledge of statistics.
Machine Learning Skills:
Machine learning is an artificial intelligence technique that allows computers to learn without being explicitly programmed. Machine learning approaches allow computers to make decisions based on prior experiences rather than requiring explicit programming for each job.
Today's world is extremely technologically advanced, and the amount of data being generated is always increasing; nonetheless, every organization wants to save time when processing this data. As a result, implementing their algorithms for each operation is extremely time-consuming. The relevance of machine learning is highlighted here, and it becomes a "must-have" talent.
Data Visualization:
Data visualizers assist individuals with varying levels of technical understanding of complex data by converting it into charts, graphs, and other visual representations.
This ability aids in the simplification of material and makes it much easier to comprehend. Companies use these talents for a variety of reasons; for example, it assists marketing teams in better understanding data and developing strategies based on it.
Data Analysis & Communication:
Data analysts must be able to evaluate vast amounts of data, spot patterns, and trends, and present the results clearly and understandably. They should also be able to share their findings with stakeholders.
Knowledge of SQL & SQL server:
The most used language for processing data in databases is SQL. It stands for Structured Query Language, and it retrieves data from database tables using commands.
SQL Server is a database management system that enables users to create tables that store data as rows with columns that reflect various aspects of each row (e.g., name, address). It also allows users to build relationships between tables using foreign keys, allowing them to delete rows from related tables when one is deleted from one table.
Before following this career path, you need to have a fundamental understanding of how SQL works.
Programming Skills:
Python is one of the most popular programming languages for data scientists since it comes with a big library of pre-built modules that make creating data manipulation and analysis tools simple. Python also supports object-oriented programming and has advanced features like dynamic typing and list comprehensions, making it excellent for handling complicated issues.
Other programming languages that one should be familiar with before pursuing a career in Data Science include C++, Java, MySQL, and others.
Creative Thinking:
To find the appropriate interpretation, data scientists must think beyond the box. They should be able to think about issues and solutions in new ways. To comprehend data and interpret it in several ways, a data scientist must be interested.
Top 10 Companies for Data Science in the USA
Data Science is on the rise! Companies are now realizing the importance of data and its impact on the business. Data Science alone gives businesses an added advantage to provide a great experience for customers. These days, more companies prefer to have dedicated Data Science teams than ever before.
Let's dive in to see who leads the pack as we present you with the top 10 data science companies in the USA that you can explore and work with:
Amazon:
In the cloud services business, Amazon Web Services (AWS) has the largest individual market share. When it comes to data science firms, Amazon is a force to be reckoned with, employing data scientists to deliver machine learning and data science solutions in addition to their AWS cloud services.
Amazon offers anti-fraud products for their online retail customers that employ machine learning to detect fraud among their abundance of transactions, in addition to their AWS-centered data science services.
There's a lot of highly intriguing and instructive data within Amazon's control, given all of the data they create and collect through their eCommerce operation. Isn't that something you'd want to have?
Amazon offers a slew of open data science jobs ranging from supply chain optimization to demand to forecast. Data scientists at Amazon have a plethora of intriguing challenges to address. Amazon has evolved from its roots as an online bookstore to become one of the top locations to work as a data scientist.
IBM:
IBM has recently announced plans to invest 240 million dollars into its Watson Group which will be used to build a new ecosystem called Watson IoT. It will help businesses use the Internet of Things (IoT) technology applications in their daily operations and make their products more efficient.
IBM has boosted its data science unit by adding more and more employees every year. It uses analytics software and services such as Hadoop and Spark that allow businesses to take advantage of massive amounts of data it collects across several industries.
IBM offers a wide variety of data science jobs at all levels of experience and education but some positions require an advanced degree in statistics or data science.
If you're looking to break into the data science industry, IBM may be a good place to start. Although the term "data science" has only been around for the last 10 years or so, it has started gaining traction in the last 5 or 6 years as an exciting new career path.
According to IBM's Director of Data Science, Andrew S. Moore, "the data revolution is transforming every part of our lives." And IBM is one of the leading organizations that are doing their part to put data science and big data at the forefront of American businesses.
Microsoft:
If you're studying data science or considering it as a career, Microsoft is an excellent choice. With their fast-paced, innovative work environment and the fact that they truly value diversity, they are an ideal company to work for if you want to make the most of your data science education.
Microsoft has been one of the top companies in each sector of technology. As far as data science is concerned, they have already made significant contributions in developing tools for analyzing data and designing algorithms that can support this type of analysis.
In addition to a good working environment, Microsoft offers competitive salaries, comprehensive benefits packages, and many other perks. They also offer generous tuition reimbursement packages. The great news is that there are many positions available at Microsoft in the data science sector.
If you want to take your career in data science to the next level, a technology company like Microsoft is one of the best places to do so.
Teradata:
Teradata is a data science company headquartered in San Francisco and with offices in New York City and Washington, DC.
Teradata is a top data science company that provides a wide range of services, including data science consulting, data migration and ETL, data warehousing, and database management. Some of its most popular products include Data Miner, Data Viewer, and SSP.
Teradata has such an extensive product line, due to this, it has been able to make a lasting impact on businesses around the world. With over a decade of experience, Teradata has worked with many different industries to provide the best solutions for their needs.
The company's clients include the likes of Marriott International and Capital One. Teradata ranks among the best companies in the industry because of its innovative approach to data science.
Cloud Era:
Cloudera is a software company that develops tools for big data technology. The company's founder, Jeff Hammer Bacher, was once an employee of Facebook and worked on the algorithms that determine what users see when they log on to their accounts.
When he left Facebook, he established Cloudera to help people use big data effectively and efficiently.
The company has since grown into something much bigger than an analytics firm—it now serves as a leader in big data management software, with over three thousand customers around the world eager to learn more about using its products.
Cloudera works with clients to develop strategies for using big data efficiently and effectively.
One of the best things about Cloudera is its commitment to transparency. You can see company salaries right on their website, which range from $74,000 to $135,000 per year. You can also see the salaries of all employees in a variety of departments.
Not only that, but They also provide several different career opportunities—if you're looking for a quick start to your data science career, Cloudera offers training and mentorship programs to help you get there.
If you already have some experience but would like to learn more about machine learning, Cloudera is an ideal place for you.
Or if you're interested in working on a more well-rounded data science project, there are plenty of opportunities to do that as well!. It is one of the best organizations to get linked with if you are interested in making a successful career in data science.
Mu Sigma:
When you think of the term "data science companies in the USA," your mind probably jumps to companies like Microsoft or Amazon. If you're looking for a data scientist job, you'll find that these big-name companies are great places to start your search.
But if you're looking for a smaller, more agile company with room for growth and the chance to make an impact on the organization's strategy—then consider Mu Sigma.
Founded in 2004 with headquarters in Chicago, IL, Mu Sigma is a data science consulting firm that uses its proprietary analytics platform, Significa™, to help businesses turn their data into actionable insight.
Over time, Mu Sigma has grown from its initial staff of 10 people to more than 1,500 employees across offices in India and the United States.
This year alone it has planned for an expansion of 600 people worldwide. It's also been named one of the fastest-growing companies by Deloitte and IBM as well as one of Fortune's 100 Best Companies to Work For.
Mu Sigma prides itself on being able to offer its employees a variety of roles and responsibilities with the opportunity to take on new challenges as they arise. As a result, each team member has his or her way of growing into a significantly better data scientist.
Facebook:
If you are looking for a data science job then you should look into the companies like this. To begin with, Facebook is one of the largest social networks that has been around for more than a decade. It's gaining popularity every year and at the moment it has over 1 billion users.
The company is another member of the famous Silicon Valley "Big Four" and it's worth over $100 billion.
The data science team on Facebook is quite powerful and their main challenge is to make sure that the overall experience of members doesn't get worse with time.
The rules of engagement are simple: if some feature turns out to be bad, it must be removed from the system; if some feature is known to be good, it must be promoted to all users as quickly as possible.
The company heavily utilizes data science skills to improve user experience and make sure that users remain happy and will come back again and again.
There are two main challenges that data scientists have to deal with – they have to keep low latency while processing billions of daily events and they have to make sure that machine learning algorithms can make sense of unstructured data that comes from user-generated content.
Splunk:
Splunk is one of the best data science companies in the US thanks to its innovative approach to big data analysis. The company builds software that helps businesses make sense of their data—whether it's collected from sensors on factory lines or information on social media—and then uses that insight to improve products or business practices.
Splunk's customers include some of the biggest names in business and technology, including eBay, Facebook, and NBCUniversal. The company has also been ranked among the top places to work by multiple sources, including Fortune magazine and Glassdoor.
Splunk attracts top data science talent from all over the US, including those from Silicon Valley tech giants such as Google and Facebook. The company has also created its program for young entrepreneurs called SPLUNK start which helps enable entrepreneurship and create new businesses based on their product solutions.
It also offers a lot of attractive job packages in data science and has a great work environment.
Numerator:
Data science companies such as Numerator are leading the way in data science job opportunities, and they've staked their claim in the United States. Their head office is located in San Francisco, with offices in New York City and Atlanta. In addition to these locations, they have a presence in Singapore, Paris, London, and Tokyo.
The company focuses on software as a service and also offers consulting services. Numerator offers a variety of services that cover all aspects of data science, including computer vision and machine learning. They also offer big data solutions for enterprise clients.
Being a successful data science company, numerator intends to maintain that position. And that is why they are constantly upgrading their team and hiring more and more skilled data scientists. It is amongst one of the most successful tech companies in the US and will surely help you on your path to becoming a well-equipped and successful data scientist.
Airbnb:
Airbnb has worked hard to revolutionize the travel sector. Data scientists have been used extensively by Airbnb. Airbnb considers data to be the customer's voice, and data science to be the interpretation of that voice. Customer-centric businesses are the ones that generally succeed. Data-driven decisions have a purpose and logic, and they tend to profit both customers and the company.
Airbnb has incorporated data science into its services and search, as well as its hiring methods. They employed data analytics to investigate and eliminate bias in their employment practices.
Airbnb is an excellent illustration of how data science firms can apply a lot of their knowledge to internal procedures. Airbnb is one of the greatest data science organizations to work for because of its culture of self-reflection and critique.
When you're planning to join such a big company you don't just plan a short-term gain, you also want to know how long you would love to stick to that role and will it remain interesting even after 3 or 5 years.
Airbnb is an innovative and very creative company and they change their pattern of work regularly to match the trends of the future. And that will ensure that you can stick around and will get different and interesting projects throughout your employment at Airbnb.
Since Airbnb is such a large and reputable company, it also offers some of the best pay in the data science industry, so that is another positive element to consider as one of the reasons why you might want to join the Airbnb data science team.
Get Certification and Boost Your Data Science Profile
Data Science is a field with fierce competition, and the skillset it requires to be a good data scientist is also not easy to acquire.
To be on par with today's advanced and experienced tech wizards, you need a good and recognized certification. Without the right mentor, the right knowledge, the right tools, and the right institution to learn from it will be very hard for you to make any good in the data science industry.
Luckily due to the rapid rise in the demand for data scientists, there are a lot of great schools & universities that are offering specialized and focused data science courses. The best universities in the USA have some of the most sought-after curricula that are going to help you in becoming a better data scientist.
You can take a bachelor's degree in data science and go after a job for that or you can continue to enrich your knowledge more and do a Master's in Data Science. You can even go for a PhD. in data science, which is sure to boost your reputation as well as give you a veteran-level status right from the start of your data science career.
Conclusion
Data Science is an enormous field with a wide array of opportunities present worldwide. The Data science industry is seeing rapid growth and with this, the demand and value of data scientists are also increasing.
The USA is one of the global leaders in the tech industry and with this, it presents you with an abundance of opportunities to work in tech fields, such as data science, software development, and many more.
To make it to the top of this industry, you will need to have proper guidance and the right education.
Lucky for you! We can help you in getting both. For any help regarding where to get the best education in data science and study abroad queries, book a call with our experts today.
